215 computer-science-intern-"https:" "https:" "https:" "https:" positions at New York University in United States
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commitment to research, innovation, and entrepreneurship that make a difference in the world. We lead and have ties to multidisciplinary centers in wireless technology, cybersecurity, urban informatics, data
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ties to multidisciplinary centers in wireless technology, cybersecurity, urban informatics, data sciences, artificial intelligence, renewable energy, and health, among others. Our faculty and students
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technology-driven research spaces, demonstrating familiarity with high-speed computing plants and related needs in data storage, utilities and unique venting requirements to support research of all types
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informatics, data sciences, artificial intelligence, renewable energy, and health, among others. Our faculty and students are part of the high-tech start-up culture in New York City and in downtown Brooklyn
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, innovation, and entrepreneurship that make a difference in the world. We lead and have ties to multidisciplinary centers in wireless technology, cybersecurity, urban informatics, data sciences, artificial
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wireless technology, cybersecurity, urban informatics, data sciences, artificial intelligence, renewable energy, and health, among others. Our faculty and students are part of the high-tech start-up culture
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and implements notification protocols. Oversees NYU's International Travel Program, to interface and monitor alerts from 3rd party providers, notify University and travelers of impending safety and
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difference in the world. We lead and have ties to multidisciplinary centers in wireless technology, cybersecurity, urban informatics, data sciences, artificial intelligence, renewable energy, and health, among
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supports technology services. Required Skills, Knowledge and Abilities: Knowledge of data warehousing technologies and data mining computational methods. Demonstrated ability to work with sensitive, personal
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and we will fill the positions on a rolling basis. Earlier applications are strongly encouraged. Education: Ph.D. in machine learning, computer science, engineering or related technical discipline